The invention relates to turbo-reception method and a turbo-receiver as may be used in a mobile communication, for example, and which apply an iterative equalization utilizing a turbo-coding technique to waveform distortions which result from interferences.
A task in the mobile station communication business is how to construct a system capable of acquiring a multitude of users on a limited frequency domain with a high quality. A multi-input multi-output (MIMO) system is known in the art as means for solving such a task. The architecture of this system is shown in FIG. 30A where a plurality of transmitters S1 to SN transmit symbols c1(i) to cN(i) at the same time and on the same frequency, and the transmitted signals are received by an MIMO receiver equipped with a plurality of antennas #1 to #M. The received signals are processed by the receiver, which estimates transmitted symbols c1(i) to cN(i) from the respective transmitters S1 to SN and delivers them separately as ĉ1(i) to ĉN(i) to output terminals Out 1 to Out N.
Up to the present time, a study of a specific implementation of an MIMO receiver in an MIMO system is not yet satisfactorily warranted. If one attempts to construct an MIMO receiver in an MIMO system on the basis of MLSE (maximum likelihood estimation) criteria, denoting the number of transmitters by N and the number of multi-paths through which a wave transmitted from each transmitter reaches the MIMO receiver by Q, the quantity of calculation required for the MIMO receiver will be on the order of 2(Q−1)N, and will increase even more voluminously with an increase in the number of transmitters N and the number of multi-paths Q. When information from a single user is transmitted as parallel signals, which are then received, a separation of individual parallel signals from each other requires a quantity of calculation, which increases exponentially with number of multi-paths. Accordingly, the present invention proposes herein an improved calculation efficiency turbo-reception method for a plurality of channel signals. To start with, an existing turbo-receiver for a single user (single transmitter) or a single channel transmitted signal, which illustrates the need for the present invention, will be described.
Turbo-receiver for Single User
An exemplary arrangement for a transmitter and a receiver is illustrated in FIG. 31. In a transmitter 10, information series c(i) is encoded in encoder 11, and an encoded output is interleaved (or rearranged) by an interleaver 12 before it is input to a modulator 13 where it modulates a carrier signal, the resulting modulated output being transmitted. The transmitted signal is received by a receiver 20 through a transmission path (each channel of multipath). In the receiver 20, a soft input soft output (SISO: single-input single output) equalizer 21 performs an equalization of delayed waves. At the input to the equalizer 21, the received signal is generally converted into a baseband, and the received baseband signal is sampled with a frequency which is equal to or greater than the frequency of symbol signals of information series in the transmitted signal to be converted into a digital signal, which is then input to the equalizer 21.
For the single user, this corresponds to N=1 in FIG. 30A, and a received output form each reception antenna #m in (m=1, 2, . . . , M) can be represented as follows:rm(k)=Σq=0Q−1hm(q)·b(k−q)+vm(k)  (1)where m represents an antenna index, h a channel value (a transmission path impulse response: a transmission path characteristic), b(k−q) a transmitted symbol from a user (transmitter 1), and vm(k) an internal thermal noise of the receiver 20. All outputs from the antennas #1 to #M are denoted by a matrix as indicated by an equation (2) to define an equation (3).r(k)=[r1(k)r2(k) . . . rM(k)]T  (2)=Σq=0Q−1H(q)·b(k−q)+v(k)  (3)wherev(k)=[v1(k)v2(k) . . . vM(k)]T  (4)H(q)=[h1(q) . . . hM(q)]T  (5)It is to be noted that [ ]T represents an inverted matrix. In cosideration of the number of channels Q of the mutipath, the following matrixes and matrix are defined:y(k)≡[rT(k+Q−1)rT(k+Q−2) . . . rT(k)]T  (6)≡H·b(k)+n(k)  (7)where
                    H        =                  [                                                                      H                                      (                    0                    )                                                                              ⋯                                                              H                                      (                                          Q                      -                      1                                        )                                                                                                                                                            0                                                                                                                                                  ⋰                                                                                                                          ⋰                                                                                                                                                  0                                                                                                                                            H                                      (                    0                    )                                                                              ⋯                                                              H                                      (                                          Q                      -                      1                                        )                                                                                ]                                    (        8        )            b(k−q)=[b(k+Q−1)b(k+Q−2) . . . b(k−Q+1)]T  (9)n(k)=[vT(k+Q−1)vT(k+Q−2) . . . vT(k)]T  (10)
r(k) as defined above is input to the SISO equalizer 21, which is a linear equalizer, deriving a log-likelihood ratio Λ1(LLR) of a probability that each encoded bit {b(i)} is equal to +1 to a probability that it is −1 as an equalization output.
                                          Λ            1                    ⁡                      [                          b              ⁡                              (                k                )                                      ]                          =                  log          ⁢                                    Pr              ⁡                              [                                                      b                    ⁡                                          (                      k                      )                                                        =                                                            +                      1                                        ❘                                          y                      ⁡                                              (                        k                        )                                                                                            ]                                                    Pr              ⁡                              [                                                      b                    ⁡                                          (                      k                      )                                                        =                                                            -                      1                                        ❘                                          y                      ⁡                                              (                        k                        )                                                                                            ]                                                                        (        11        )            ≡λ1[b(k)]+λ2p[b(k)]  (12)
where λ1[b(k)] represents an extrinsic information fed to a succeeding decoder 24 and λ2P[b(k)] a priori information applied to the equalizer 21. The log-likelihood ratio Λ1[b(k)] is fed to a subtractor 22 where the a priori information λ2[b(k)] is subtracted therefrom. The result is then fed through a deinterleaver 23 to an SISO channel decoder 24, which calculates a log-likelihood ratio Λ2 as follows:
                                          Λ            2                    ⁡                      [                          b              ⁡                              (                i                )                                      ]                          =                  log          ⁢                                    Pr              ⁡                              [                                                                            b                      ⁡                                              (                        i                        )                                                              =                                                                  +                        1                                            ❘                                                                        λ                          1                                                ⁡                                                  [                                                      b                            ⁡                                                          (                              i                              )                                                                                ]                                                                                                      ,                                      i                    =                    0                                    ,                  …                  ⁢                                                                          ,                                      B                    -                    1                                                  ]                                                    Pr              ⁡                              [                                                                            b                      ⁡                                              (                        i                        )                                                              =                                                                  -                        1                                            ❘                                                                        λ                          1                                                ⁡                                                  [                                                      b                            ⁡                                                          (                              i                              )                                                                                ]                                                                                                      ,                                      i                    =                    0                                    ,                  …                  ⁢                                                                          ,                                      B                    -                    1                                                  ]                                                                        (        13        )            B: frame length≡λ2[b(i)]+λ1p[b(i)]  (14)where λ2[b(i)] represents an extrinsic information which is applied as λ2P[b(k)] to the equalizer 21 during the iteration, while λ1[b(k)] is applied as a priori information λ1P[b(i)] to the decoder 24. In a subtractor 25, λ1[b(i)] is subtracted from Λ2[b(i)], and the result is fed through an interleaver 26 to the equalizer 21 and the subtractor 22. In this manner, the equalization and the decoding are iterated to achieve an improvement of an error rate.
To describe the prestage equalizer 21 in detail, the calculation of a linear filter response applied to a received matrix y(k) will be described. Using the a priori information λ2P[b(k)] for the equalizer 21, a soft decision symbol estimateb′(k)=tan h[λ2P[b(k)]/2]  (15)is calculated. Using the estimate and a channel matrix H, an interference component or a replica H·b′(k) of the interference component is reproduced and subtracted from the received signal. Thus,y′(k)≡y(k)−H·b′(k)  (16)=H·(b(k)−b′(k))+n(k)  (17)where,b′(k)=[b′(k+Q−1) . . . 0 . . . b′(k−Q+1)]T  (18)Because the replica H·b′(k) of the interference component cannot be always a correct replica, the interference component cannot be completely eliminated by the equation (16). So a linear filter coefficient w(k) which eliminates any residue of the interference component is determined according to the MMSE (minimum mean square error) technique indicated below.w(k)=arg min ∥wH(k)y′(k)−b(k)∥2  (19)where H represents a conjugate transposition and ∥ ∥ a norm. w(k) which mimimizes the equation (19) is determined.
Deriving w(k) in this manner is described in Daryl Reynolds and Xiandong Wang, “Low Complexity Turbo-Equalization for Diversity Channels” (http:/ee.tamu.edu/Reynolds/). A major achievement of this technique lies in a significant reduction in the quantity of calculation. The quantity of calculation according to a conventional MLSE turbo has been proportional to the order of 2Q−1 while a suppression to the order of Q3 is enabled by this technique. It will be seen that wH(k)·y′(k) represents an output from the equalizer 21, and is used to calculate λ1[b(k)], which is then fed through the deinterleaver 23 to the decoder 24 to be used in the decoding calculation.
For purpose of equalization in the equalizer 21, it is necessary to estimate the channel value (transmission path impulse response) h appearing in the equation (1). This estimation is hereafter referred to as a channel estimation. The channel estimation takes place by using a received signal of a known training series such as a unique word which is transmitted as a leader of one frame and a stored training series. A poor accuracy of the channel estimation prevents an equalization in the equalizer 21 from occurring in a proper manner. The accuracy of the channel estimation can be enhanced by increasing the proportion which the training series occupies in one frame, but this degrades the transmission efficiency of the intended data. Accordingly, it is desirable that the accuracy of the channel estimation could be improved while reducint the proportion of the training series in one frame.
This is not limited to a receiver for multiple channel transmitted signals inclusive of MIMO, but the same is true in the channel estimation of a receiver such as RAKE receiver or a receiver using an adaptive array antenna where the certainty of a decoded result is improved by an iterative decoding process.
The described turbo-receiver has following restrictions:                It is an accommodation for a single user (single transmitter) or only one series transmitted signal.        A channel value (matrix H) is necessary in reproducing an interference component, and this must be estimated in actual implementions. An estimation error results in a degradation in the effect of an iterative equalization.        
It is an object of the invention to provide compensations for these two restrictions by providing a turbo-reception method and a receiver therefor which allow the receiver mentioned above to be extended to a receiver for a plurality of transmitted series signals such as for multiple users or parallel transmissions from a single user.
It is another object of the invention to provide a reception method and a receiver therefor in which a channel value of a received signal is estimated from the received signal and a known signal serving as a reference signal, the received signal is processed using the estimated channel value, and the processed signal is decoded so that the processing using the estimated channel value and the decoding are iterated upon the same received signal and which allow the channel estimation to be achieved with good accuracy using a relatively short known signal.